July 29, 2010 | When patients experience organ failure, there are several points “where clinical experts would agree that a biomarker panel, based on minimally invasive sources like blood or urine, would be extremely useful for consistently and sensitively predicting whether or not a patient would experience immune rejection.”

That’s what Bruce McManus, director of the PROOF (Prevention of Organ Failure) Centre of Excellence, and the James Hogg iCAPTURE Research Centre—both at the University of British Columbia in Vancouver, Canada—says. To that end, a major focus at the two centres involves developing biomarkers for heart, lung, and kidney failure. This year, both were joint recipients of Bio-IT World’s Best Practices Award for Personalized and Translational Medicine.

The centers were nominated by IO Informatics. PROOF and iCAPTURE began collaborating with the company in 2008, as they sought to functionally link their multiple experimental data to better understand organ failure. IO Informatics’ Sentient Suite software played a key role in integrating, contextualizing (in terms of other published data), and analyzing these data.

There were several phases to the project, explains Erich Gombocz, IO Informatics’ CSO. “Knowledge Explorer,” part of the Sentient Suite, was used to build a common ontology bringing together different data sets at PROOF and iCAPTURE and visualizing these in a meaningful fashion. “Web Query” facilitated advanced searching and secure sharing of data and results through a common web interface, while “Process Manager,” proved essential for managing experimental and clinical samples across multiple analytical steps. Biological networks being complex affairs, the team simplified matters by first creating basic, graphical SPARQL queries from the data. They then turned these queries into ASK (Applied Semantic Knowledgebase) arrays of models for both acute organ rejection and non-rejection, complete with scoring function to allow confident decisions on the part of clinicians, when screening patients for pre-symptomatic organ failure.

“SPARQL queries are the gem here,” says Raymond Ng, CIO at PROOF. “They can be used to explore relationships among specific genes, proteins, and metabolites identified in our so-called ‘combinatorial biomarker panels.’” Such exploration is essential for understanding why the identified biomarker panels are effective, he explains; they can then generate new biological hypotheses which could lead to novel targets for therapy.

The researchers at UBC were particularly pleased with Sentient Suite’s excellent visual rendering of their data—on any correlation map, for example, proteins were depicted as mini three-dimensional shapes, not unlike the actual molecules. Relationship lines between data sets had varying thicknesses, indicating correlation strength. “It’s one thing to have computational scientists talk to one another, and quite another to provide tools allowing everyone to understand the same concepts, McManus says.

That the Sentient Suite provides an interface both intuitive and easy to use gets another thumbs-up from the Vancouver group. “Ease of use, or lack thereof, is a showstopper,” Ng says. “In this regard, IO Informatics’ software is top of the line.”

Ng frankly admits that he and his colleagues figured the Best Practices competition was, at best, a long shot. “Raymond was almost speechless; we were all delighted and very excited,” McManus says. “It [our collaboration] illustrates, although not uniquely, the sort of public-private partnership that’s needed if you’re really going to make a difference in sorting through the complexities that exist with disease risk.”

This article also appeared in the July-August 2010 issue of Bio-IT World Magazine. Subscriptions are free for qualifying individuals. Apply today.